Steadiness

Steadiness tells you how consistent a layer has been across saved results. It is not the same thing as the baseline itself.

The baseline answers, "What pattern shows up most often?" Steadiness answers, "How consistently does that pattern keep showing up across retakes?"

As more results are saved, Myndora can compare how often the same outcome returns versus how often competing outcomes appear. Larger gaps point to a steadier pattern. Smaller gaps point to more variation or uncertainty.

That is why retakes matter so much. They do not just give you more data. They help the product estimate whether a layer is settling into a clear pattern or still moving around.

On overview pages and dashboard summaries, Myndora shows steadiness as part of the fuller layer picture. The first result page is about the current session. The overview is where consistency across time becomes visible.

In practice, that means you can see not only your usual result, but also how firmly that result is supported by the history of retakes so far.

A result can be interesting even when steadiness is low, but it should be read more cautiously. Lower steadiness can mean the pattern is still mixed, context-sensitive, or not yet measured enough times to feel settled.

Higher steadiness makes a layer more dependable inside the wider profile and gives more weight to the way it interacts with other layers and product features.